Comments (3)
You can use predict(model, newdata = ....................., type = "labels")
to get predictions. It will give you cosine or dot product similarity measures between your text and the categories.
There are really many R packages which give classification metrics, I think the evaluation metrics in Starspace are not so valuable. Look at R packages on CRAN which give you standard classification metrics or multi-label classification metrics.
If you really want to use the starspace test mode, you can use what is coded here https://github.com/bnosac/ruimtehol/blob/master/src/rcpp_textspace.cpp#L377 and call that as follows: ruimtehol:::textspace_evaluate(model$model, testFile = "path-to-file-containing-testdata", basedoc = "this is really optional", predictionFile = "path-to-output-file", int K = 5)
but at your own discretion (might crash, I have been testing this out but forgot myself how to call this functionality because you should create your own evaluation functionality on your downstream task).
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Thanks. I'll give that a try. I was using the predict
before. Was just wondering if the Starspace test method was available.
Thanks for the quick response.
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Closing as answer was given. Feel free to reopen if needed.
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Related Issues (20)
- find a way to solve Inf values in starspace_embedding due to numeric overflow
- Sentence separator for labelDoc format HOT 9
- Prediction of next word in a sentence HOT 6
- see if we can use proxyC https://cran.r-project.org/web/packages/proxyC/index.html for similarities instead of the current embedding_similarity implementation HOT 1
- Is it possible to exclude similarity of e.g. sentences when predicting? HOT 8
- unable to train wikipedia_shuf_train5M.txt HOT 2
- make function as_fasttext, using code from embed_tagspace
- allow option to use softmax to get probability-like results when using predict alongside model trained with embed_tagspace
- Running ruimtehol on R server HOT 18
- embed_tagspace produces different results within a session and when loaded (starspace_load_model) if ngrams is used HOT 11
- Problems with running ruimtehol on Windows R HOT 4
- non-virtual destructor
- example of manual calculation of embedding of doc
- Option of weighting words HOT 3
- Checkpointing: Continue model training at epoch x after saving intermediate model HOT 2
- Word embeddings HOT 6
- StarSpace Models in Shiny App HOT 8
- R CMD check FAIL on r-devel windows HOT 1
- switch to C++17 instead of C++11 as by cran policy HOT 1
- Request for sentiment scoring example HOT 1
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